While most agencies were able to quickly provide a public listing of all their datasets, several appear to be struggling with the release requirement — keeping the public in the dark about what information they truly hold.

Disclaimer: The opinions expressed by the guest blogger and those providing comments are theirs alone and do not reflect the opinions of the Sunlight Foundation or any employee thereof. Sunlight Foundation is not responsible for the accuracy of any of the information within the guest blog.

Irina Bolychevsky is the Product Owner of CKAN -- data management system that makes data accessible – by providing tools to streamline publishing, sharing, finding and using data. (@CKANproject) is the leading open source data management platform, at the Open Knowledge Foundation (@OKFN). She led and managed the new release of data.gov from the CKAN team and previously managed the relaunch of data.gov.uk. Follow her on twitter: @shevski.

A huge milestone was reached yesterday with the relaunch of the U.S. government data portal on a single, open source platform. A joint collaboration between a small UK team at the Open Knowledge Foundation and data.gov, this was an ambitious project to reduce the numerous previous catalogs and repositories into one central portal for serious re-use of government open data.

Catalog.data.gov brings together both geospatial as well as “raw” (tabular or text) data under a single roof in a consistent standardised beautiful interface that can be searched, faceted by fomat, publisher, community or keyword as well as filtered by location.

Users can quickly and easily find relevant or related data (no longer a metadata XML file!), download it directly from the search results page or preview spatial map layers or CSV files in the browser.

Of course, there is still work to do, especially about improving the data quality, but nonetheless a vast amount of effort went into metadata cleanup, hiding records with no working links and adding a flexible distributed approval workflow to allow review of harvested datasets pre-publication.